u/Ok-Bike-1037

This might just be me, but AI coding tools have made some PRs weirdly harder to review.

The code usually looks clean at first glance, but then you find small logic issues, overcomplicated helpers, weird edge cases, or tests that pass but don’t really prove anything. It feels less like reviewing someone’s thought process and more like trying to guess what the tool assumed.

I still use AI for coding, so this is not an anti-AI rant. It’s just that review feels different now.

Anyone else noticing this? How are you changing your review process?

Even if you like local AI, there are probably still some things where cloud AI is better.

For me, the question is not really local vs cloud. It is more about knowing which tasks are worth keeping local and which ones need the strongest model possible.

What do you still use cloud AI for?

And what tasks have you fully moved to local AI?

Search inside personal files is still pretty bad for a lot of people.

You know you wrote something, saved a PDF, or had a note somewhere, but finding it later is annoying.

Local AI could be useful here if it can search and explain your own files without uploading them.

Do you think local AI can become a better personal search engine?

Or is normal keyword search still more reliable?

One thing that confuses new users is hardware.

Some people say local AI works fine on a laptop, others say you need a strong GPU, lots of RAM, or Apple Silicon.

For normal use like chat, writing, summaries, and notes, what hardware do you think is the real minimum?

Not for huge models, just something that feels usable day to day.

Local AI has gotten a lot better, but it still has some rough edges.

For me, the annoying parts are usually setup, model downloads, knowing which model to use, slow responses on weaker hardware, and apps that feel more like demos than daily tools.

What still frustrates you about local AI apps?

And what would make you use them more often?